MR‐BOIL: Causal inference in one‐sample Mendelian randomization for binary outcome with integrated likelihood method
Sign Up to like & getrecommendations! Published in 2023 at "Genetic Epidemiology"
DOI: 10.1002/gepi.22520
Abstract: Mendelian randomization is a statistical method for inferring the causal relationship between exposures and outcomes using an economics‐derived instrumental variable approach. The research results are relatively complete when both exposures and outcomes are continuous variables.… read more here.
Keywords: boil; mendelian randomization; causal; method ... See more keywords
Conditional validation sampling for consistent risk estimation with binary outcome data subject to misclassification
Sign Up to like & getrecommendations! Published in 2019 at "Pharmacoepidemiology and Drug Safety"
DOI: 10.1002/pds.4701
Abstract: Misclassification of a binary outcome can introduce bias in estimation of the odds‐ratio associated with an exposure of interest in pharmacoepidemiology research. It has been previously demonstrated that utilizing information from an internal randomly selected… read more here.
Keywords: misclassification; conditional validation; estimation; binary outcome ... See more keywords
A note on estimating the Cox-Snell R2 from a reported C statistic (AUROC) to inform sample size calculations for developing a prediction model with a binary outcome.
Sign Up to like & getrecommendations! Published in 2020 at "Statistics in medicine"
DOI: 10.1002/sim.8806
Abstract: In 2019 we published a pair of articles in Statistics in Medicine that describe how to calculate the minimum sample size for developing a multivariable prediction model with a continuous outcome, or with a binary… read more here.
Keywords: sample size; model; prediction model; binary outcome ... See more keywords
Logistic regression with misclassification in binary outcome variables: a method and software
Sign Up to like & getrecommendations! Published in 2017 at "Behaviormetrika"
DOI: 10.1007/s41237-017-0031-y
Abstract: Measurement error in continuous, normally distributed data is well known in the literature. Measurement error in a binary outcome variable, however, remains under-studied. Misclassification is the error in categorical data in which the observed category… read more here.
Keywords: logistic regression; misclassification; regression misclassification; model ... See more keywords
The binary-outcome detection loophole
Sign Up to like & getrecommendations! Published in 2021 at "New Journal of Physics"
DOI: 10.1088/1367-2630/ac10a5
Abstract: The detection loophole problem arises when quantum devices fail to provide an output for some runs. If treating these devices in a device-independent manner, failure to include the unsuccessful runs in the output statistics can… read more here.
Keywords: detection; bell inequality; detection threshold; outcome detection ... See more keywords
Clinically relevant factors associated with a binary outcome of diabetic macular ischaemia: an OCTA study
Sign Up to like & getrecommendations! Published in 2022 at "British Journal of Ophthalmology"
DOI: 10.1136/bjophthalmol-2021-320779
Abstract: Aims We investigated the demographic, ocular, diabetes-related and systemic factors associated with a binary outcome of diabetic macular ischaemia (DMI) as assessed by optical coherence tomography angiography (OCTA) evaluation of non-perfusion at the level of… read more here.
Keywords: factors associated; level; dmi; binary outcome ... See more keywords
Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework
Sign Up to like & getrecommendations! Published in 2019 at "BMC Medical Research Methodology"
DOI: 10.1186/s12874-019-0673-4
Abstract: BackgroundChoosing the most performing method in terms of outcome prediction or variables selection is a recurring problem in prognosis studies, leading to many publications on methods comparison. But some aspects have received little attention. First,… read more here.
Keywords: methodology; outcome; outcome setting; binary outcome ... See more keywords
Enrichment Bayesian design for randomized clinical trials using categorical biomarkers and a binary outcome
Sign Up to like & getrecommendations! Published in 2022 at "BMC Medical Research Methodology"
DOI: 10.1186/s12874-022-01513-z
Abstract: Background Adaptive clinical trials have been increasingly commonly employed to select a potential target population for one trial without conducting trials separately. Such enrichment designs typically consist of two or three stages, where the first… read more here.
Keywords: clinical trials; binary outcome; randomized clinical; design randomized ... See more keywords